Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.5194/acp-17-5751-2017 |
Satellite-derived methane hotspot emission estimates using a fast data-driven method | |
Buchwitz, Michael1; Schneising, Oliver1; Reuter, Maximilian1; Heymann, Jens1; Krautwurst, Sven1; Bovensmann, Heinrich1; Burrows, John P.1; Boesch, Hartmut2,3; Parker, Robert J.2,3; Somkuti, Peter2,3; Detmers, Rob G.4; Hasekamp, Otto P.4; Aben, Ilse4; Butz, Andre5,6; Frankenberg, Christian7,8; Turner, Alexander J.9 | |
2017-05-09 | |
发表期刊 | ATMOSPHERIC CHEMISTRY AND PHYSICS
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ISSN | 1680-7316 |
EISSN | 1680-7324 |
出版年 | 2017 |
卷号 | 17期号:9 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany; England; Netherlands; USA |
英文摘要 | Methane is an important atmospheric greenhouse gas and an adequate understanding of its emission sources is needed for climate change assessments, predictions, and the development and verification of emission mitigation strategies. Satellite retrievals of near-surface-sensitive column-averaged dry-air mole fractions of atmospheric methane, i.e. X CH4, can be used to quantify methane emissions. Maps of time-averaged satellite-derived X CH4 show regionally elevated methane over several methane source regions. In order to obtain methane emissions of these source regions we use a simple and fast data-driven method to estimate annual methane emissions and corresponding 1 sigma uncertainties directly from maps of annually averaged satellite X CH4. From theoretical considerations we expect that our method tends to underestimate emissions. When applying our method to high-resolution atmospheric methane simulations, we typically find agreement within the uncertainty range of our method (often 100 %) but also find that our method tends to underestimate emissions by typically about 40 %. To what extent these findings are model dependent needs to be assessed. We apply our method to an ensemble of satellite X CH4 data products consisting of two products from SCIAMACHY/ENVISAT and two products from TANSO-FTS/GOSAT covering the time period 2003-2014. We obtain annual emissions of four source areas: Four Corners in the south-western USA, the southern part of Central Valley, California, Azerbaijan, and Turkmenistan. We find that our estimated emissions are in good agreement with independently derived estimates for Four Corners and Azerbaijan. For the Central Valley and Turkmenistan our estimated annual emissions are higher compared to the EDGAR v4.2 anthropogenic emission inventory. For Turkmenistan we find on average about 50% higher emissions with our annual emission uncertainty estimates overlapping with the EDGAR emissions. For the region around Bakersfield in the Central Valley we find a factor of 5-8 higher emissions compared to EDGAR, albeit with large uncertainty. Major methane emission sources in this region are oil/gas and livestock. Our findings corroborate recently published studies based on aircraft and satellite measurements and new bottom-up estimates reporting significantly underestimated methane emissions of oil/gas and/or livestock in this area in EDGAR. |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000425848100001 |
WOS关键词 | HIGH-SPATIAL-RESOLUTION ; CARBON-DIOXIDE ; CO2 EMISSIONS ; SENTINEL-5 PRECURSOR ; ATMOSPHERIC METHANE ; RETRIEVAL ALGORITHM ; CH4 EMISSIONS ; FOSSIL-FUEL ; TANSO-FTS ; SCIAMACHY |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/20607 |
专题 | 地球科学 |
作者单位 | 1.Univ Bremen, Inst Environm Phys IUP, Bremen, Germany; 2.Univ Leicester, Earth Observat Sci, Leicester, Leics, England; 3.NERC, Natl Ctr Earth Observat, Leicester, Leics, England; 4.SRON, Netherlands Inst Space Res, Utrecht, Netherlands; 5.KIT, Karlsruhe, Germany; 6.LMU, Munich, Germany; 7.CALTECH, Div Geol & Planetary Sci, Pasadena, CA 91125 USA; 8.Jet Prop Lab, Pasadena, CA USA; 9.Harvard Univ, Sch Engn & Appl Sci, Cambridge, MA 02138 USA |
推荐引用方式 GB/T 7714 | Buchwitz, Michael,Schneising, Oliver,Reuter, Maximilian,et al. Satellite-derived methane hotspot emission estimates using a fast data-driven method[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2017,17(9). |
APA | Buchwitz, Michael.,Schneising, Oliver.,Reuter, Maximilian.,Heymann, Jens.,Krautwurst, Sven.,...&Turner, Alexander J..(2017).Satellite-derived methane hotspot emission estimates using a fast data-driven method.ATMOSPHERIC CHEMISTRY AND PHYSICS,17(9). |
MLA | Buchwitz, Michael,et al."Satellite-derived methane hotspot emission estimates using a fast data-driven method".ATMOSPHERIC CHEMISTRY AND PHYSICS 17.9(2017). |
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